Identification using biometrics has become an increasingly popular form of user verification. A “biometric” is generally understood to refer to one or more intrinsic physical traits or characteristics associated with an individual (e.g., facial features, fingerprint, etc.). The increase in popularity of such a verification approach is due to the inherent advantages of biometric data. First, it is convenient for individuals and institutions because an individual no longer needs to remember passwords and/or carry unique identifiers such as photo identification cards. Biometrics are compact and individuals can easily carry their identity with them at all times. Another key advantage of using biometrics is security.
At first glance, biometric data is incredibly secure because, theoretically, no two individuals possess the same biometric signature. However, although biometric identification is undoubtedly unique and simple to use, the biometrics of an individual can also be easily compromised. Biometric forgery can be as simple as hacking into an accounts database and copying the biometric signatures of individuals. Furthermore, after obtaining a biometric signature, a forger can easily infiltrate any account secured by the biometric (e.g., banks, computers, buildings, etc.).
Many existing techniques do not address biometric theft since many assume that the uniqueness of biometric signatures alone provides sufficient security. However, as a practical issue, after the biometric of an individual has been stolen, the individual can not simply cancel the stolen biometric and establish a new one. There have been attempts to create distorted versions of a biometric for identification purposes, however, these methods can be limited. For example, some existing techniques utilize a method of distorting biometrics by warping the entire biometric. Other existing techniques utilize a method of distorting biometrics by breaking the biometric up into blocks and scrambling the blocks of the biometric.
These existing distortion approaches result in a biometric form that can not be used on current biometric scanners because the biometric no longer resembles the scanned body part. Further, the distorted biometric is so obviously altered that a biometric forger may make attempts to reverse engineer the original biometric. This is feasible since existing systems create distorted biometric forms that can revert to the original biometric. Therefore, if a forger knows that a biometric has been distorted and knows how the biometric was distorted, the forger can undo the distortion.
The method of scrambling pieces of a biometric is typically used in face biometrics. Such an existing technique creates Picasso-type face renderings that can not be used on legacy face recognition systems because the images are too abstract. It follows that such an existing technique fails to distort face biometrics in such a way that characteristics of a “natural” face are retained.
Therefore, there is a need for generating distorted face biometrics that: (1) are unique; (2) can not be used to reform the original biometric (“non-invertible”); (3) appear authentic or natural; (4) can be consistently recreated; and (5) can be easily canceled and replaced whenever the security or privacy of an individual has been compromised.